Updates
Model and report changes
- We have extended the use of serological sampling data to use samples taken beyond the first wave of the pandemic. The samples are those collected by NHS Blood and Transplant using the Roche-N assay, which measures the prevalence of infection-acquired antibodies in the population.
- The model now accounts for the ongoing immunisation programme, stratifying the population of people still susceptible to infection with the virus according to their immunisation status (unimmunised/1 dose/2 doses). We use data on the daily proportions of the population getting immunised to inform this splitting of the population, assuming that it takes three weeks for vaccine-derived immunity to develop. Vaccine efficacy is assumed against both infection and death, using values for the efficacy in agreement with those found here. We have a changepoint in the vaccine efficacy on the 10th May, which marks a transition from alpha being the dominant variant, to delta.
- The model also accounts for a different susceptibility to infection in each adult age group (no prior information is used); and for the under-15s, (using prior information from Viner et al, 2020, which estimates children to be less likely to acquire infection when in contact with an infectious individual).
- The model has the ability to incorporate estimates of community prevalence, by region and age group, from the Office of National Statistics COVID-19 Infection Survey (see Data Sources for details). These are included weekly since the outset of the Survey in May 2020 for the age groups >4 years to inform trends in incidence that are too recent to be captured by the data on deaths.
- The underlying probability of an unvaccinated individual dying following infection with SARS-CoV2 (the infection-fatality rate, IFR) is allowed to change gradually over the course of 30 days every (approximately) 100 days. This is designed to reflect fluctuations due to seasonal effects, demand on healthcare services or the emergence of new virus variants of differing severity.
- The ‘Epidemic summary’ only reports the current value for the IFR by age. To visualise how this has changed over time in our model, see the IFR tab in the ‘Infections and Deaths’ section of the report. The quantity that is now plotted under this tab is the probability of dying if infected, taking into account the impact of the immunisation programme - it is an average of a lower rate of death in vaccinated individuals and a higher rate among the unvaccinated.
Updated findings
- The estimated number of new daily infections on the 12th November across England is 46,600 (40,400–53,600, 95% credible interval). The daily infection rate is estimated to be 83 per 100k population per day nationally. The highest rates are now in the East Midlands (EM) and the West Midlands (WM) with 131 and 118 infections per 100K population, corresponding to 6,270 and 6,960 daily infections respectively. These are followed by the rates in the East of England (EE) and Yorkshire and Humber (YH), which are 94 and 92 infections per 100k respectively. The North East (NE) and the South West (SW) have daily infection rates around 80 per 100k, while the South East (SE) and London (GL) have rates between 60-70 infections per 100k. The North West (NW) continues to have the lowest infection rates at 47 infections per 100k. Note that a substantial proportion of these infections will be asymptomatic.
- The daily number of deaths is now estimated to be declining, such that we forecast between 91 and 152 deaths per day by the 3rd of December.
- This week it is unlikely that Rt is bigger than 1 in any region, with no recovery in the values of Rt following the school half-term holiday. There is a 21% chance that Rt>1 in EM, but this is 6% or less everywhere else.
- The growth rate for England remains at -0.02 (-0.01– -0.03) per day. This means that, nationally, the number of infections is decreasing, corresponding to an Rt of around 0.85.
- Our estimates for the attack rate, that is the proportion of the regional populations who have ever been infected, have NE at 59% and GL at 57%. WM, YH and NW are all also above the national average with 54%, 51% and 51% respectively.The SE and SW continue to have the lowest attack rates at 37% and 36%. These correspond to a very slight downward revision to last week.
- Note that the deaths data used are only very weakly informative on Rt over the last two weeks. Therefore, the estimate for current incidence, Rt and the forecast of daily numbers of deaths are likely to be subject to some revision.
Interpretation
- Our estimates show a pandemic with Rt values that have slightly decreased from last week, remaining below 1. This could, in part, still be a legacy of the half-term school holiday. As anticipated in last week’s report, the number of deaths appear to have peaked at 157 deaths per day, much lower than the peaks of the first two waves of infection.
- Plots of the IFR over time show that from the end of January we estimate a decreasing IFR in all adult age groups, but most steeply in the older ages. This drop indicates the benefits of immunisation against death over and above the benefits against infection. Following this drop, there has been a period of plateau followed by a gradual increase in the overall IFR to 0.26% (0.26%–0.27%). However, the age-specific IFRs appear to be falling, suggesting that the overall increase is due to shifting age patterns towards older people being infected. The estimated IFR is highest in the over-75s at 3.2% (3.0%–3.4%)
- For context, in addition to the data used here, the number of reported new positive tests (by date of specimen) has increased this week in comparison to last week, though this would be as expected following the national half-term holiday. As a caveat to this, trends in the number of reported cases are highly dependent on the volume and targeting of testing, the public’s testing behaviour and significant reporting delays, and therefore are difficult to interpret. Overall, there have been 8.1million positive tests, which, compared to our estimate of incidence, would suggest around 1 in 3 infections have been identified. This seems plausible, particularly when considering the low ascertainment rates of the first wave. Hospitalisations are no longer increasing, while the prevalence of infection, as estimated by the ONS Coronavirus Infection Survey, has decreased markedly, falling to 1.7%% in England.
Summary
Real-time tracking of an epidemic, as data accumulate over time, is an essential component of a public health response to a new outbreak. A team of statistical modellers at the MRC Biostatistics Unit (BSU), University of Cambridge, are working to provide regular now-casts and forecasts of COVID-19 infections and deaths. This information feeds directly to the SAGE sub-group, Scientific Pandemic Influenza sub-group on Modelling (SPI-M), and to regional Public Health England (PHE) teams.
Methods
We fit a transmission model (Birrell et al. 2020) to a number of data sources (see ‘Data Sources’), to reconstruct the number of new COVID-19 infections over time in different age groups and NHS regions, estimate a measure of ongoing transmission and predict the number of new COVID-19 deaths.
Data sources
We use:
- Data on COVID-19 confirmed deaths from the Public Health England (PHE) line-listing This consists of a combination of deaths notified to:
- the Demographics Batch Service (DBS), a mechanism that allows PHE to submit a file of patient information to the National Health Service spine for tracing against the personal demographics service (PDS). PHE submit a line list of patients diagnosed with COVID-19 to DBS daily. The file is returned with a death flag and date of death updated (started 20th March, 2020).
- NHS England, who report data from NHS trusts relating to patients who have died after admission to hospital or within emergency department settings.
- Health Protection Teams (HPTs), resulting from a select survey created by PHE to capture deaths occurring outside of hospital settings, e.g. care homes (started 23rd March, 2020)
- Data on antibody prevalence in blood samples from a PHE survey of NHS Blood Transfusion (NHSBT) donors.
Data are stratified into eight age groups: <1, 1-4, 5-14, 15-24, 25-44, 45-64, 65-74, 75+, and the NHS England regions (North East and Yorkshire, North West, Midlands, East of England, London, South East, South West).
- Published information on the the natural history of COVID-19 (Verity et al., 2020; Li et al, 2020)
- Information on contacts between different age groups from:
- A Survey that describes relative rates of contacts between different age groups (Mossong et al. 2008).
- Google Community Mobility reports, informing the changes in people’s mobility over the course of the pandemic, particularly after the March 23rd lockdown measures.
- The ONS’ time use survey, which in conjunction with the google mobility study, allows estimation of the changing exposure to infection risk over time.
- Data from the Department for Education describing the proportion of children currently attending school.
- Daily data on the numbers of people getting immunised by age-group and region. These data are derived from the National Immunisation Management Service (NIMS). These data includes all COVID-19 immunisations administered at hospital hubs, local immunisation service sites such as GP practices, and dedicated immunisation centres.
Epidemic summary
Current \(R_t\)
Value of \(R_t\), the average number of secondary infections due to a typical infection today.
Attack rate
The percentage of a given group that has been infected.
Change in infections incidence
Growth rates
NB: negative growth rates are rates of decline. Values are daily changes.
| England |
-0.02 |
-0.03 |
-0.01 |
| East of England |
-0.02 |
-0.04 |
0.00 |
| East Midlands |
-0.01 |
-0.03 |
0.01 |
| London |
-0.02 |
-0.04 |
0.00 |
| North East |
-0.02 |
-0.05 |
0.00 |
| North West |
-0.03 |
-0.05 |
0.00 |
| South East |
-0.02 |
-0.04 |
0.00 |
| South West |
-0.04 |
-0.06 |
-0.02 |
| West Midlands |
-0.01 |
-0.03 |
0.00 |
| Yorkshire and The Humber |
-0.02 |
-0.04 |
0.00 |
Halving times
Halving times in days, if a region shows growth than value will be NA.
| England |
36.96 |
26.65 |
58.53 |
| East of England |
31.35 |
16.12 |
215.35 |
| East Midlands |
103.70 |
26.57 |
NA |
| London |
30.10 |
15.75 |
293.54 |
| North East |
28.06 |
13.40 |
339.12 |
| North West |
26.74 |
13.49 |
237.84 |
| South East |
29.89 |
16.28 |
141.10 |
| South West |
16.97 |
11.36 |
32.00 |
| West Midlands |
49.06 |
21.77 |
NA |
| Yorkshire and The Humber |
36.65 |
18.16 |
439.09 |
Doubling times
Doubling times in days, if a region shows decline then the value will be NA.
| England |
NA |
NA |
NA |
| East of England |
NA |
NA |
NA |
| East Midlands |
NA |
57.19 |
NA |
| London |
NA |
NA |
NA |
| North East |
NA |
NA |
NA |
| North West |
NA |
NA |
NA |
| South East |
NA |
NA |
NA |
| South West |
NA |
NA |
NA |
| West Midlands |
NA |
305.81 |
NA |
| Yorkshire and The Humber |
NA |
NA |
NA |
Change in deaths incidence
Growth rates
NB: negative growth rates are rates of decline. Values are daily changes.
| England |
-0.01 |
-0.01 |
0.00 |
| East of England |
0.00 |
-0.02 |
0.01 |
| East Midlands |
0.00 |
-0.01 |
0.02 |
| London |
-0.01 |
-0.02 |
0.00 |
| North East |
-0.01 |
-0.02 |
0.01 |
| North West |
-0.01 |
-0.03 |
0.00 |
| South East |
-0.01 |
-0.02 |
0.00 |
| South West |
-0.02 |
-0.03 |
-0.01 |
| West Midlands |
0.00 |
-0.01 |
0.01 |
| Yorkshire and The Humber |
-0.01 |
-0.02 |
0.01 |
Halving times
Halving times in days, if a region shows growth than value will be NA.
| England |
93.38 |
59.08 |
239.62 |
| East of England |
141.37 |
39.53 |
NA |
| East Midlands |
NA |
68.34 |
NA |
| London |
68.37 |
32.69 |
NA |
| North East |
82.66 |
29.97 |
NA |
| North West |
48.60 |
25.21 |
NA |
| South East |
56.15 |
31.40 |
503.85 |
| South West |
39.75 |
24.42 |
119.79 |
| West Midlands |
NA |
54.71 |
NA |
| Yorkshire and The Humber |
126.31 |
37.82 |
NA |
Doubling times
Doubling times in days, if a region shows decline then the value will be NA.
| England |
NA |
NA |
NA |
| East of England |
NA |
80.17 |
NA |
| East Midlands |
179.12 |
37.81 |
NA |
| London |
NA |
224.23 |
NA |
| North East |
NA |
85.16 |
NA |
| North West |
NA |
493.86 |
NA |
| South East |
NA |
NA |
NA |
| South West |
NA |
NA |
NA |
| West Midlands |
1909.83 |
52.64 |
NA |
| Yorkshire and The Humber |
NA |
77.16 |
NA |
## The execution of the prevalence code block will proceed if
## prev.dat exists and this is TRUE
## it is not and external report and this is FALSE
Infections and deaths
The shaded areas show periods of national lockdown, the green lines the dates (once confirmed) of the steps in the roadmap in the UK Governement’s COVID-19 Response – Spring 2021, and the red line shows the date these results were produced (12 Nov).
Prob \(R_t > 1\)
The figure below shows the probability that \(R_t\) is greater than 1 (ie: the number of infections is growing) in each region over time. Clicking the regions in the legend allows lines to be added or removed from the figure.
Copyright © MRC Biostatistics Unit, University of Cambridge